It sometimes occurs that, in devices that attempt to match fingerprints or similar data structures, collecting fingerprint or similar information can be subject to errors or noise. One form of errors can occur when the user's finger has abrasions, gaps, pits, scratches, or other damage to its outer layer. These artifacts can affect a fingerprint sensor negatively, particularly in that they can cause the capacitance measured by the sensor to be measured abnormally. For example, the in the region of such artifacts, the fingerprint sensor might measure an abnormally high capacitance or an abnormally low capacitance, either way causing a fingerprint image derived from the sensor to be difficult to match against a database of known fingerprints.
One possible response to measurement, by the sensor, of an abnormally high capacitance or an abnormally low capacitance, is to re-measure the capacitance of the user's finger, such as with other parameters for measuring capacitance. While this technique might generally have the benefit of obtaining a fingerprint image that is less subject to problems due to these artifacts, it is subject to the drawback of taking substantial time to re-measure the capacitance of the user's finger. During this substantial time the user might grow impatient, move his finger, or otherwise degrade the operation of the fingerprint sensor.
It also sometimes occurs that, in devices that attempt to sense image data, such as fingerprints and similar image data, collecting image data can be subject to a substantial level of fixed pattern noise. Collected image data can include artifacts, whether of the nature of the image or of the nature of the method of collection of image data. For example, fingerprint image data can include vertical bars in the image. In such cases, it might occur that blocks or tiles of multiple elements of image data can include one (or more) lines that have a maximum grayscale level, as if a black line had been drawn on the image data. Blocks may be 8×8, 10×10, or any other suitable size, and need not be square.
In such cases, it might also occur that adjacent elements of image data can include one (or more) lines that have a maximum greyscale level, as though a black shape of arbitrary area had been drawn on the image data. In other cases, it might also occur that one (or more) lines can be present in a block of image data, but not so many lines that the block of image data cannot be used. In such cases, it might also occur that the fixed pattern noise is more significant than the raw data, such as wherein the image data might be read by a sensor at values near 200 microvolts, while the fixed pattern noise might be read by the same sensor at values near 10 millivolts. This fixed pattern noise can pose a particular problem in that large noise values can reduce the device's sensitivity to midrange grayscale levels, in an effort to distinguish differing noise levels.
Each of these examples, as well as other possible considerations, can cause one or more difficulties as a result of excessive cost (such as time or processing power required) to image or match fingerprints.